Computational Optimization and Applications

, Volume 62, Issue 1, pp 5–29 | Cite as

Low-rank retractions: a survey and new results



Retractions are a prevalent tool in Riemannian optimization that provides a way to smoothly select a curve on a manifold with given initial position and velocity. We review and propose several retractions on the manifold \({\mathcal {M}}_r\) of rank-\(r\)\(m\times n\) matrices. With the exception of the exponential retraction (for the embedded geometry), which is clearly the least efficient choice, the retractions considered do not differ much in terms of run time and flop count. However, considerable differences are observed according to properties such as domain of definition, boundedness, first/second-order property, and symmetry.


Low-rank manifold Fixed-rank manifold Low-rank optimization Retraction Geodesic Quasi-geodesic Projective retraction Orthographic retraction Lie–Trotter splitting 



We are grateful to the anonymous referees and to Bart Vandereycken for several useful comments on the first version of this paper. This work was financially supported by the Belgian FRFC (Fonds de la Recherche Fondamentale Collective). The work of I.O. was supported by Russian Science Foundation Grant 14-11-00659


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Mathematical Engineering, ICTEAM InstituteUniversité catholique de LouvainLouvain-la-NeuveBelgium
  2. 2.Skolkovo Institute of Science and TechnologyMoscowRussia

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